Discretize factors?

Update,

I have it working, but now its producing really ugly labels.  Must be a
small adjustment to the code.  Any ideas??

##Create example data.frame
group<- c("A", "B","B","C","C","C")
a<- c(1,4,3,4,5,6)
b<- c(5,4,5,3,4,5)
d<- data.frame(cbind(a,b,group))

#create new frame with discretized group

cbind(d[,1:2], model.matrix(~0+d[,3]) )

   a b d[, 3]A d[, 3]B d[, 3]C
1 1 5       1       0       0
2 4 4       0       1       0
3 3 5       0       1       0
4 4 3       0       0       1
5 5 4       0       0       1
6 6 5       0       0       1


So, as you can see, it works, but the labels for the groups don't

I then tried using the column name instead of number and still got ugly
results:

cbind(d[,1:2], model.matrix(~0+d[,"group"]) )

   a b d[, "group"]A d[, "group"]B d[, "group"]C
1 1 5             1             0             0
2 4 4             0             1             0
3 3 5             0             1             0
4 4 3             0             0             1
5 5 4             0             0             1
6 6 5             0             0             1



Any ideas?

-N



On 5/15/10 11:02 AM, Noah Silverman wrote:

Hi,

I'm looking for an easy way to discretize factors in R

I've noticed that the lm function does this automatically with a nice
result.

If I have

group<- c("A", "B","B","C","C","C")

and run:

lm(result ~ x1 + group)

The lm function has split the group into separate binary variables {0,1}
before performing the regression.  I now have:
groupA
groupB
groupC

Some of the other models that I want to try won't accept factors, so
they need to be discretized this way.

Is there a command in R for this, or some easy shortcut?  (I tried
digging into the lm code, but couldn't find where this is being done.)

Thanks!

-N